An Adaptable Human Vision Model for Subjective Video Quality Rating Prediction Among CIF, SD, HD and E-CINEMA. A new highly adaptable model for predicting human vision response is presented for enabling an improved method of predicting subjective video quality. The ability to adapt enables comparison of video with dissimilar image sizes, viewing environments, frame rates, video quality classes, etc. (for example HD vs. SD vs. CIF). Model test results are compared with human response

The Human Vision Model.pdf

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